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International audience; Galileo E1C, the pilot component of the E1 Open Service signal (CBOC(6,1,1/11) modulation), Galileo E5a and GPS L5 (BPSK(10) modulation) are signals that will be used by civil aviation receivers for pseudorange computation. To meet stringent requirements defined for civil aviation GNSS receivers, the characterization of distortions which could affect a GNSS signal in a hazardous way is required. In particular, expected signal distortions generated at payload level are described by Threat Models (TMs). Distortions incorporated in the TM are also called Evil WaveForm (EWF).These TMs, and their associated parameter ranges, referred to as Threat Space (TS), are powerful and necessary tools to design and test the performance of Signal Quality Monitor (SQM). The SQM is a mean to detect the presence of dangerous signal distortions and is necessary to protect users with high requirements in terms of integrity, accuracy, availability, and continuity (for example civil aviation users). Nowadays, this monitoring task is performed by GBAS and SBAS reference stations for GPS L1 C/A to warn the user in a timely manner. In this paper, SQMs for Galileo E1C and Galileo E5a will be designed and compared using a new representation introduced in [1]. Using this representation, different SQMs are compared and an optimized SQM is proposed to monitor signal distortions on Galileo E5a and Galileo E1C signals.

International audience; This paper analyses two ways to investigate nominal distortions of GNSS signals. Firstly, these perturbations can be observed from the correlation function point of view and secondly, from the CDO (Chip domain observable) which is a way to extract the shape of such distortions directly from the digitized signal samples using the code periodicity. This method is also known as the Vision Correlator (NovAtel). [1]These two techniques are compared in terms of capacity to observe and characterize GNSS signal nominal deformations. The CDO has the advantage to process only one specific part of the signal whereas the correlation function observable is less affected by the noise and is directly linked with the pseudorange estimation. As a conclusion, this publication proposes a new way to perform the Signal Quality Monitoring based on the Chip Domain Observable.